An Average Enumeration Method of Hyperspectral Imaging Data for Quantitative Evaluation of Medical Device Surface Contamination

Published

September 15, 2014

Author(s)

Hanh Le, Moon Kim, Jeeseong C. Hwang, Yi Yang, Pawneena U-Thainual, Jin Kang, Do-Hyun Kim

Abstract

We propose a quantification method called Mapped Average Principal component analysis Score (MAPS) to enumerate the contamination coverage on common medical device surfaces. The method was adapted from conventional Principal Component Analysis (PCA) on non-overlapped regions of a full frame hyperspectral image to resolve the percentage of contamination from the substrate. The concept was proven by using a controlled contamination sample with artificial test soil and color simulating organic mixture, and was further validated using a bacterial system including biofilm on stainless steel surface. We also validate the results of MAPS with other statistical spectral analysis including Spectral Angle Mapper (SAM). The proposed method provides an alternative quantification method for hyperspectral imaging data, which can be easily implemented by basic PCA analysis.

Citation

Biomedical Optics Express

Volume

5

Issue

10

Pub Type

Journals

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DOI Link

Keywords

multispectral imaging, hyperspectral imaging, medical device, contamination, biofilm

Citation

Le, H. , Kim, M. , Hwang, J. , Yang, Y. , U-Thainual, P. , Kang, J. and Kim, D. (2014), An Average Enumeration Method of Hyperspectral Imaging Data for Quantitative Evaluation of Medical Device Surface Contamination, Biomedical Optics Express, [online], https://doi.org/10.1364/BOE.5.003613 (Accessed December 14, 2024)